A Lightweight Approach to Localization for Blind and Visually Impaired Travelers
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We present a localization algorithm based on computer vision and inertial sensing; the algorithm is lightweight in that it requires only a 2D floor plan of the environment, annotated with the locations of visual landmarks and points of interest, instead of a detailed 3D model (used in many computer vision localization algorithms), and requires no new physical infrastructure (such as Bluetooth beacons). The algorithm can serve as the foundation for a wayfinding app that runs on a smartphone; crucially, the approach is fully accessible because it doesn’t require the user to aim the camera at specific visual targets, which would be problematic for BVI users who may not be able to see these targets. In this work, we improve upon the existing algorithm so as to incorporate recognition of multiple classes of visual landmarks to facilitate effective localization, and demonstrate empirically how localization performance improves as the number of these classes increases
本研究提出一种基于计算机视觉与惯性传感的定位算法。该算法具备轻量化特性:仅需搭载标注有视觉地标与兴趣点位置的环境二维平面图,而非诸多计算机视觉定位算法所依赖的精细三维模型,且无需新增物理基础设施(如蓝牙信标)。该算法可作为智能手机端寻路应用的核心支撑;尤为关键的是,该方案具备全可访问性:无需用户将摄像头对准特定视觉目标——这一点对无法看清目标的视力障碍(Blind or Visually Impaired, BVI)用户而言曾是显著使用障碍。本研究对现有算法进行改进,加入多类别视觉地标识别功能以实现高效定位,并通过实证实验验证了随着此类地标类别数量增加,定位性能的提升趋势。




